longwide transforms data from long to wide format. Ideal for
transforming output from growthcleanr::cleangrowth() into a format suitable
longwide( long_df, id = "id", subjid = "subjid", sex = "sex", agedays = "agedays", param = "param", measurement = "measurement", gcr_result = "gcr_result", include_all = FALSE, inclusion_types = c("Include"), extra_cols = NULL, keep_unmatched_data = FALSE )
A data frame to be transformed. Expects columns: id, subjid, sex, agedays, param, measurement, and gcr_result.
name of observation ID column
name of subject ID column
name of sex descriptor column
name of age (in days) descriptor column
name of parameter column to identify each type of measurement
name of measurement column containing the actual measurement data
name of column of results from growthcleanr::cleangrowth()
Determines whether the function keeps all exclusion codes. If TRUE, all exclusion types are kept and the inclusion_types argument is ignored. Defaults to FALSE.
Vector indicating which exclusion codes from the cleaning algorithm should be included in the data, given that include_all is FALSE. For all options, see growthcleanr::cleangrowth(). Defaults to c("Include").
Vector of additional columns to include in the output. If a column C1 differs on agedays matched height and weight values, then include separate ht_C1 and wt_C1 columns as well as a match_C1 column that gives booleans indicating where ht_C1 and wt_C1 are the same. If the agedays matched height and weight columns are identical, then only include a single version of C1. Defaults to empty vector (not keeping any additional columns).
boolean indicating whether to keep height/weight observations that do not have a matching weight/height on that day
Returns a data frame transformed from long to wide. Includes only values flagged with indicated inclusion types. Potentially includes additional columns if arguments are passed to extra_cols. For each subject, heights without corresponding weights for a given age (and vice versa) will be dropped unless keep_unmatched_data is set to TRUE.
# Run on a small subset of given data df <- as.data.frame(syngrowth) df <- df[df$subjid %in% unique(df[, "subjid"])[1:2], ] df <- cbind(df, "gcr_result" = cleangrowth(df$subjid, df$param, df$agedays, df$sex, df$measurement)) # Convert to wide format wide_df <- longwide(df) # Include all inclusion types wide_df <- longwide(df, include_all = TRUE) # Specify all inclusion codes wide_df <- longwide(df, inclusion_types = c("Include", "Exclude-Carried-Forward"))